fdoperezi,github

neuroevolution

Simple Neuroevolution to Solve the CartPole Environment

neuromancer

Pytorch-based framework for solving parametric constrained optimization problems, physics-informed system identification, and parametric model predictive control.

nextml

IJulia notebooks for the Next.ML event on 1/17/2015

nla-skoltech-project

nlp_quickbook

NLP in Python with Deep Learning

nlp_yelp_review_unsupervised

Train unsupervised LDA Topic Model on raw Yelp review text, use topic distributions as feature inputs to supervised classifier of review sentiment

nni

An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.

nnproject_deepmask

Deep Neural Network for object segmentation.

nolearn

Abstractions around neural net libraries, most notably Lasagne.

nonrandomwalks

Implementation of Lo and MacKinlay's statistical tests from A Non Random Walk Down Wall Street

notebooks

nucleotide-transformer

🧬 Nucleotide Transformer: Building and Evaluating Robust Foundation Models for Human Genomics

numer.ai

Validation and prediction code for numer.ai

numerox

Numerai tournament toolbox written in Python

nupic

Numenta Platform for Intelligent Computing: a brain-inspired machine intelligence platform, and biologically accurate neural network based on cortical learning algorithms.

nupic-fall2014-music-composer-fingerprinting

result of nupic fall 2014 hackathon, midi music composer fingerprinting with Numenta's online unsupervissed cortical learning algorithm. (http://numenta.org/nupic.html)

nupic.core

Implementation of core NuPIC algorithms in C++ (under construction)

nupic.critic

Music critic hack from 2014 Spring Hackathon

nupic.geospatial

NuPIC demo app for geospatial anomaly detection.

nupic.regression

Regression test suite for NuPIC

nupic.rogue

nvtabular

NVTabular is a feature engineering and preprocessing library for tabular data designed to quickly and easily manipulate terabyte scale datasets used to train deep learning based recommender systems.